CN110954080A - Magnetic compass calibration method for eliminating carrier magnetic interference - Google Patents

Magnetic compass calibration method for eliminating carrier magnetic interference Download PDF

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CN110954080A
CN110954080A CN201911358750.5A CN201911358750A CN110954080A CN 110954080 A CN110954080 A CN 110954080A CN 201911358750 A CN201911358750 A CN 201911358750A CN 110954080 A CN110954080 A CN 110954080A
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magnetic
carrier
axis
field data
magnetic field
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吕冰
孟诚
邓超凡
伍东凌
童卫平
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710th Research Institute of CSIC
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710th Research Institute of CSIC
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C17/00—Compasses; Devices for ascertaining true or magnetic north for navigation or surveying purposes
    • G01C17/38—Testing, calibrating, or compensating of compasses

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Abstract

The invention discloses a magnetic compass calibration method for eliminating carrier magnetic interference, which comprises the following steps: acquiring three-axis magnetic field data of a magnetic compass under different postures of a carrier platform; establishing an error model between the three-axis magnetic field data before and after the three-axis magnetic sensor is calibrated, and solving error parameters of the three-axis magnetic sensor in the error model by using the three-axis magnetic field data to obtain an error model; and thirdly, acquiring triaxial magnetic field data and triaxial acceleration data of the magnetic compass again, substituting the acquired triaxial magnetic field data of the magnetic compass into the error model to obtain calibrated triaxial magnetic field data, solving by combining the triaxial acceleration data to obtain a pitch angle, a roll angle and an azimuth angle of the magnetic compass, and outputting a calibrated attitude angle of the magnetic compass. The invention can output high-precision carrier azimuth angles.

Description

Magnetic compass calibration method for eliminating carrier magnetic interference
Technical Field
The invention belongs to the technical field of navigation, and particularly relates to a magnetic compass calibration method for eliminating carrier magnetic interference.
Background
The magnetic compass resolves azimuth angles by using measured geomagnetic field data in three-axis directions, and has the advantages of small volume, low power consumption, high reliability, high precision, low price and the like, so that the magnetic compass is widely applied to the fields of aviation, navigation, vehicle-mounted and various viewing and aiming equipment. When the magnetic compass is installed on various carrier platforms for application, ferromagnetic objects such as batteries, cables, motors, steel structural members and the like exist on most of the carrier platforms, and the ferromagnetic objects can greatly influence the azimuth angle measurement accuracy of the magnetic compass. Therefore, in order to improve the azimuth angle measurement accuracy of the magnetic compass on the carrier platform, a magnetic compass calibration method suitable for the carrier platform needs to be designed, hard magnetic interference and soft magnetic interference existing in the carrier platform are calibrated, the influence of the magnetic interference on the magnetic compass is eliminated, and therefore the azimuth angle of the carrier platform is accurately calculated.
Disclosure of Invention
In view of this, the invention provides a magnetic compass calibration method for eliminating carrier magnetic interference, which can output a high-precision carrier azimuth angle.
The invention is realized by the following technical scheme:
a magnetic compass calibration method for eliminating carrier magnetic interference comprises the following steps:
acquiring three-axis magnetic field data of a magnetic compass under different postures of a carrier platform;
establishing an error model between the three-axis magnetic field data before and after the three-axis magnetic sensor is calibrated, and solving error parameters of the three-axis magnetic sensor in the error model by using the three-axis magnetic field data to obtain an error model;
and thirdly, acquiring triaxial magnetic field data and triaxial acceleration data of the magnetic compass again, substituting the acquired triaxial magnetic field data of the magnetic compass into the error model to obtain calibrated triaxial magnetic field data, solving by combining the triaxial acceleration data to obtain a pitch angle, a roll angle and an azimuth angle of the magnetic compass, and outputting a calibrated attitude angle of the magnetic compass.
Further, the solution method of the azimuth angle is as follows: converting the calibrated three-axis magnetic field data into X, Y-axis magnetic field data under a horizontal coordinate system; and then substituting the magnetic field data in the X, Y axis direction under the horizontal coordinate system into a magnetic azimuth calculation formula to solve the magnetic compass azimuth.
Further, the error model in the second step is established by using a poisson model.
Further, the solving method of the error parameters of the three-axis magnetic sensor in the second step specifically includes:
and taking two norms of the error model to be arranged as a measurement equation of a Kalman filter, taking error parameters of a three-axis magnetic sensor in the error model as state vectors of the Kalman filter, taking a unit matrix as a state transition matrix of the Kalman filter, establishing the Kalman filter equation, solving the Kalman filter equation by utilizing three-axis magnetic field data under more than twelve different postures, and solving to obtain an estimation value of the state vectors, namely the error parameters of the three-axis magnetic sensor.
Further, the method for solving the pitch angle and the roll angle in the third step comprises the following steps: and calculating by using the transformation relation between the geographic coordinate system and the carrier coordinate system.
Further, the acquisition method of the carrier platform for different postures is as follows:
if the carrier platform is a handheld carrier, rotating the carrier platform in the space, and dynamically acquiring and outputting more than twelve groups of three-axis magnetic field data at fixed time intervals; or changing the posture of the carrier platform, statically acquiring more than twelve groups of three-axis magnetic field data and outputting the data.
Further, the method for rotating in the space comprises the following steps: and (3) carrying the carrier by hand, firstly enabling the carrier platform to slowly rotate for one circle around the Z-axis direction of the vertical axis, then rotating for one circle around the Y-axis direction of the pitching axis, and finally rotating for one circle around the X-axis direction of the transverse rolling shaft.
Further, if the carrier platform is calibrated in a plane, rotating the carrier platform in the plane, and dynamically acquiring and outputting more than eight groups of three-axis magnetic field data at fixed time intervals; or changing the posture of the carrier platform, statically acquiring more than eight groups of three-axis magnetic field data and outputting the data.
Has the advantages that:
the method can realize the calibration of the hard magnetic interference and the soft magnetic interference existing on the carrier platform and output the high-precision carrier azimuth angle, and the calibration method does not need complex precision equipment, utilizes the algorithm built in the magnetic compass and combines a plurality of groups of acquired data for calibration, and has simple operation and high calibration efficiency.
Drawings
FIG. 1 is a schematic diagram of the magnetic compass attitude angle and coordinate system definition;
FIG. 2 is a schematic diagram of attitude placement of a magnetic compass space multi-point calibration method;
FIG. 3 is a schematic diagram of the attitude placement of the magnetic compass plane by the multipoint calibration method;
FIG. 4 is a flow chart of magnetic compass calibration and azimuth calculation.
Detailed Description
The invention is described in detail below by way of example with reference to the accompanying drawings.
The magnetic compass is composed of a triaxial magnetic sensor, a triaxial acceleration sensor and a data acquisition and processing system, wherein the triaxial magnetic sensor is used for measuring triaxial direction magnetic field data, and the triaxial acceleration sensor is used for measuring triaxial direction acceleration data.
The present embodiment provides a calibration method for a magnetic compass that eliminates carrier magnetic interference, wherein a geographic coordinate system refers to a local north-east coordinate system, and is different from general geographic coordinate system definitions in that an X axis of the geographic coordinate system points to magnetic north rather than true north, a Y axis and the X axis point to east vertically, and a Z axis points downward along a horizontal plane vertical direction. The carrier coordinate system is a coordinate system relatively fixed with the carrier platform, the magnetic compass is installed along the carrier coordinate system, the X axis of the carrier coordinate system points to the front along the longitudinal axis of the carrier, the Y axis points to the right along the transverse axis of the carrier, and the Z axis is downward and forms a right-hand coordinate system with the X, Y axis. As shown in fig. 1, the azimuth angle measurement range is 0-360 degrees, 0 degrees when pointing to magnetic north, and clockwise rotation is positive; the pitch angle measuring range is-90 degrees, the horizontal angle is 0 degree, the upward head raising is positive, and the downward head lowering is negative; the transverse roll angle measuring range is-180 degrees, the horizontal angle is 0 degree, the right inclination is positive, and the left inclination is negative; the arrow direction of the magnetic compass is a forward direction and corresponds to an X axis of the three-axis magnetic sensor and an A axis of the three-axis acceleration sensor, the right direction of the magnetic compass corresponds to a Y axis of the three-axis magnetic sensor and a B axis of the three-axis acceleration sensor, and the vertical downward direction of the magnetic compass corresponds to a Z axis of the three-axis magnetic sensor and a C axis of the three-axis acceleration sensor.
Because the carrier coordinate system and the geographic coordinate system are not coincident under most conditions, and the azimuth angle of the carrier is solved by using the magnetic field data in the directions of the X axis and the Y axis under the geographic coordinate system for calculation, the azimuth angle α can be solved only by transforming the three-axis magnetic field data under the carrier coordinate system to the geographic coordinate system by using the attitude rotation matrix.
According to the Euler rotation relation, obtaining a matrix representation of the conversion relation between the carrier coordinate system and the geographic coordinate system:
Figure BDA0002336626630000041
wherein β is a pitch angle, γ is a roll angle, and α is an azimuth angle.
The calculation method of the pitch angle β and the roll angle gamma is that the earth gravity acceleration has no projection component in the horizontal direction in the geographic coordinate system, and the value of the triaxial acceleration sensor only in the C-axis direction is not zero and is g:
Figure BDA0002336626630000042
in the formula (I), the compound is shown in the specification,
Figure BDA0002336626630000043
is a triaxial acceleration value measured under a magnetic compass carrier coordinate system,
Figure BDA0002336626630000044
and (3) developing the formula (2) to obtain a coordinate rotation matrix from the geographic coordinate system to the carrier coordinate system:
Figure BDA0002336626630000051
by solving equation (3), the pitch angle β and roll angle γ can be calculated:
Figure BDA0002336626630000052
Figure BDA0002336626630000053
the three-axis magnetic field values measured under the carrier coordinate system are respectively HX、HY、HZLet the azimuth α be 0 in equation (1), and use the coordinate rotation matrix
Figure BDA0002336626630000054
H is to beX、HY、HZObtaining two-axis magnetic field values in the horizontal direction respectively M by transforming to a geographic coordinate systemX、MYThe corresponding calculation formula is shown in formula (6).
MX＝HXcosβ+HYsinβsinγ+HZsinβcosγ
MY＝HYcosγ-HZsinγ(6)
Obtaining a two-axis magnetic field value M in the horizontal direction in the geographic coordinate system, namely in the horizontal coordinate systemX、MYThen, the magnetic compass azimuth can be calculated by using the magnetic azimuth calculation formula (7).
α＝arctan2(MX,MY) (7)
It can be seen from the above formula that to calculate the accurate azimuth angle of the magnetic compass, the accurate triaxial magnetic field value under the carrier coordinate system must be acquired, and since there may exist hard magnetic interference and soft magnetic interference on the carrier platform, these magnetic interferences must be eliminated, so as to ensure that the measurement precision of the carrier azimuth angle measured by the magnetic compass can meet the requirements of the corresponding technical indexes.
If the magnetic compass is installed on a small-sized carrier platform for use, such as a handheld carrier, and the azimuth angle needs to be measured under a large inclination angle of the carrier in the use process, the hard magnetic interference and the soft magnetic interference existing on the carrier platform can be calibrated by adopting a space multipoint calibration method or a space rotation calibration method.
The three-axis magnetic field data (data before calibration) directly acquired by the magnetic compass is assumed to be maga＝[BXBYBZ]TAnd the triaxial magnetic field data obtained after calibration is magb＝[HXHYHZ]TAnd constructing an error model according to the Poisson model as shown in a formula (8).
magb＝K(maga+Z) (8)
In the formula, K is a parameter matrix formed by sensitivity errors and non-orthogonality errors of the three-axis magnetic sensor, and Z is a parameter matrix formed by zero offset errors of the three-axis magnetic sensor.
The two-norm of the formula (8) is selected and arranged to obtain the formula (9),
Figure BDA0002336626630000061
in the calibration process, the magnetic compass is put in a certain area to acquire data at various postures, and the geomagnetic field | mag of the areabThe parameter c of the model is solved by using the known value of | l1～c10Done by Kalman filtering, c1～c10For three-axis magnetic sensor error parameters, the parameter matrix K, Z is formed from three-axis magnetic sensor error parameters c1～c10And (4) forming.
The state vector of the kalman filter is:
X＝[c1c2c3c4c5c6c7c8c9c10]T
and taking the formula (9) as a measurement equation of the Kalman filter, wherein a state transition matrix of the Kalman filter is an identity matrix I.
After a Kalman filter system state equation XI and a measurement equation are established, a basic equation of a Kalman filter solving process is shown as a formula (10).
Figure BDA0002336626630000062
Where k is the number of times data is input in the calculation, Qk-1A variance matrix of a Kalman filter system noise sequence; rkA variance matrix for the measured noise sequence;
Figure BDA0002336626630000063
and Pk-1Estimating an initial value, phi, for the state of the filterk,k-1In order to be a filter state transition matrix,
Figure BDA0002336626630000064
for filtered state one-step prediction, Pk/k-1For one-step prediction of the mean square error, KkIn order to obtain the gain of the kalman filter,
Figure BDA0002336626630000065
for filter state estimation, PkFor state estimation error, ZkIs a state quantity, i.e. | | magb||，HkIn order to measure the matrix, the measurement matrix is,
Figure BDA0002336626630000071
is a measurement equation. Measurement matrix HkFrom the equation (9), the measurement equation
Figure BDA0002336626630000072
In (a) contains c1～c10。
As shown in FIG. 4, initial filter values are given
Figure BDA0002336626630000073
And P0Collecting magnetic compass three-axis magnetic field data B under more than twelve different posturesX、BY、BZInputting the data into a Kalman filter equation (10), and calculating the state estimation of the k moment in a recursion way
Figure BDA0002336626630000074
Derived estimation of Kalman filter state vectorsValue of
Figure BDA0002336626630000075
I.e. the parameter c to be solved1～c10。
Obtain the parameter c1～c10Then, the error model for calibrating the three-axis magnetic field data is obtained in the formula (8).
The triaxial magnetic field data of the magnetic compass are collected again, and the triaxial magnetic field data before calibration is substituted into a formula (8) to obtain calibrated triaxial magnetic field data HX、HY、HZThen, the azimuth α of the magnetic compass is calculated by the equations (6) to (7).
The magnetic compass calibration and attitude angle calculation method is a built-in algorithm of the magnetic compass and does not need other precise instruments.
Calculated parameter c1～c10The accuracy of the method depends on whether the Kalman filter measurement input data can be uniformly and stably distributed in the space. Theoretically, in order to obtain more accurate parameters, a minimum of 10 sets of measurement input data are needed, and the more measurement input data, the more parameter c is calculated1～c10The more accurate, but in the actual calibration process, the larger the measurement input data volume, the lower the calculation efficiency, and the more the workload of acquiring data will be increased. Generally, 12-32 groups of data are collected to accurately calculate the model parameters.
In order to facilitate the user to carry out space calibration work, two calibration methods of space multi-point calibration and space rotation calibration are designed.
For the spatial multi-point calibration method, the carrier platform can be placed in postures as shown in fig. 2, relevant data are statically acquired in each posture, and only the pitch angle state is shown in a side view. The attitude angle of each attitude of the carrier platform is described as follows:
pose 1 represents: enabling the azimuth angle of the carrier to point to 0 degree, the pitch angle to be 0 degree and the roll angle to be 45 degrees;
pose 2 represents: the azimuth angle of the carrier is pointed to 90 degrees, the pitch angle is 0 degree, and the roll angle is minus 45 degrees;
pose 3 represents: the azimuth angle of the carrier is enabled to point to 180 degrees, the pitch angle is 0 degree, and the roll angle is 45 degrees;
pose 4 represents: enabling the azimuth angle of the carrier to point to 270 degrees, the pitch angle to be 0 degree and the roll angle to be-45 degrees;
pose 5 represents: the azimuth angle of the carrier is pointed to 30 degrees, the pitch angle is 45 degrees, and the roll angle is 45 degrees;
pose 6 represents: the azimuth angle of the carrier is pointed to 120 degrees, the pitch angle is 45 degrees, and the roll angle is-45 degrees;
pose 7 represents: the azimuth angle of the carrier is pointed to 210 degrees, the pitch angle is 45 degrees, and the roll angle is 45 degrees;
pose 8 represents: the azimuth angle of the carrier is enabled to point to 300 degrees, the pitch angle is 45 degrees, and the roll angle is minus 45 degrees;
pose 9 represents: the azimuth angle of the carrier is pointed to 60 degrees, the pitch angle is minus 45 degrees, and the roll angle is 45 degrees;
pose 10 represents: the azimuth angle of the carrier is pointed to 150 degrees, the pitch angle is minus 45 degrees, and the roll angle is minus 45 degrees;
pose 11 represents: the azimuth angle of the carrier is pointed to 240 degrees, the pitch angle is minus 45 degrees, and the roll angle is 45 degrees;
pose 12 represents: the azimuth angle of the carrier is pointed to 330 degrees, the pitch angle is minus 45 degrees, and the roll angle is minus 45 degrees.
The following are specifically mentioned:
a) the spatial multi-point calibration method of the embodiment includes, but is not limited to, spatial 12-point calibration, and more gestures can be added according to actual conditions to acquire corresponding data;
b) the azimuth angle expressed in the above-mentioned key points of posture arrangement does not refer to the absolute azimuth angle of the carrier platform, but refers to a relative angle, for example, when the posture 1 is arranged, the azimuth angle of the magnetic compass can point to any angle, for example, 42 °, but when the posture 2 is arranged, the azimuth angle of the magnetic compass needs to be arranged to be about 132 °, and so on;
c) the pitch angle and the roll angle expressed in the above-mentioned attitude placing key points refer to absolute angles of the carrier platform relative to a horizontal plane, but when the attitude placing key points are placed in the above attitudes, the values of azimuth angle, pitch angle and roll angle do not need to be particularly strict, and the error of each angle can be accepted within +/-15 degrees;
d) in some application scenes, when the carrier is placed in a posture, the carrier can be placed without applying a roll angle, only the azimuth angle and the pitch angle of the carrier are placed according to the description, and the specific angle for placing the pitch angle of the carrier can be adjusted according to the actual condition;
e) the postures 1 to 12 are described above for convenience, and the data acquisition sequence is not limited in the actual operation process.
For the spatial rotation calibration method, the calibration is implemented according to the following steps: and (3) holding the carrier by hand, firstly slowly rotating the carrier for one circle at a constant speed (rotating azimuth angle) in the Z-axis direction of the vertical axis, then slowly rotating the carrier for one circle at a constant speed (rotating pitch angle) in the Y-axis direction of the pitch axis, and finally slowly rotating the carrier for one circle at a constant speed (rotating roll angle) in the X-axis direction of the roll axis. In the process of uniform and slow rotation, the magnetic compass automatically sends related commands at fixed intervals, and dynamically acquires triaxial magnetic field data in the rotating process.
After data acquisition is finished, the magnetic compass built-in algorithm can automatically finish space multipoint calibration or space rotation calibration, an error model is solved, the obtained calibration parameters are stored, the obtained parameters are carried into a formula (8) to obtain calibrated triaxial magnetic field data, and then a real-time azimuth α of the carrier is obtained by calculation through a formula (7).
If the carrier platform installed by the magnetic compass only needs to measure the azimuth angle of the carrier in a nearly horizontal state, a plane multipoint calibration method or a plane circumference calibration method can be adopted to calibrate the hard magnetic interference and the soft magnetic interference existing on the carrier platform.
Considering that the acquired data are all data in a nearly horizontal state and lack of magnetic field data related to the Z axis in the plane calibration process, the formula (8) is taken as a two-norm to be arranged to obtain a formula (11):
d1W1 2+d2W2 2+d3W1W2+d4W1W3+d5W2W3+d6W1+d7W2＝||magb|| (11)
in the formula (d)1～d7As error parameters of model planar three-axis magnetic sensor, W1、W2、W3The three-axis magnetic field data measured by the magnetic compass three-axis magnetic sensor X-axis, Y-axis and Z-axis respectively, in the calibration process, the carrier rotates in a certain area to collect data of all directions, and the geomagnetic field | mag in the area isb| is a known value, and the parameter d is solved1～d7This can be done by kalman filtering, the state vector of which is:
X＝[d1d2d3d4d5d6d7]T
and taking the formula (11) as a measurement equation of the Kalman filter, wherein a state transition matrix of the Kalman filter is an identity matrix I.
After a Kalman filter system state equation and a measurement equation are established, a basic equation of a Kalman filter solving process is shown as a formula (12).
Figure BDA0002336626630000101
Where k is the number of times data is input in the calculation, Qk-1A variance matrix of a Kalman filter system noise sequence; rkA variance matrix for the measured noise sequence;
Figure BDA0002336626630000102
and Pk-1Estimating an initial value, phi, for the state of the filterk,k-1In order to be a filter state transition matrix,
Figure BDA0002336626630000103
for filtered state one-step prediction, Pk/k-1For one-step prediction of the mean square error, KkIn order to obtain the gain of the kalman filter,
Figure BDA0002336626630000104
for filter state estimation, PkState estimation error, HkIn order to measure the matrix, the measurement matrix is,
Figure BDA0002336626630000105
is a measurement equation. Measurement matrix HkFrom equation (11), the measurement equation
Figure BDA0002336626630000106
In (a) contains d1～d7。
Setting initial value of filter
Figure BDA0002336626630000107
And P0Collecting three-axis magnetic field data W under more than eight different posturesX、WY、WZInputting the data into a Kalman filter equation (12), and calculating the state estimation of the k moment in a recursion way
Figure BDA0002336626630000108
Obtaining the estimated value of the Kalman filter state vector after inputting all measured data
Figure BDA0002336626630000109
I.e. the parameter d to be solved1～d7。
Calculated parameter d1～d7The accuracy of the method depends on whether the Kalman filter measurement input data can be uniformly and stably distributed in a plane. Theoretically, in order to obtain more accurate parameters, a minimum of 7 sets of measurement input data are needed, and the more measurement input data, the more parameter d is calculated1～d7The more accurate, but in the actual calibration process, the larger the measurement input data volume, the lower the calculation efficiency, and the more the workload of acquiring data will be increased. Generally, the model parameters can be accurately calculated by collecting data of 8-24 postures in a plane.
In order to facilitate a user to carry out plane calibration work, two calibration methods of plane multipoint calibration and plane circumference calibration are designed.
For the planar multipoint calibration method, the carrier platform can be placed in postures as shown in fig. 3, relevant data are statically acquired in each posture, and only the pitch angle state is shown in the side view. The attitude angle of each attitude of the carrier platform is specifically described as follows:
pose 1 represents: enabling the azimuth angle of the carrier to point to 0 degree, the pitch angle to be 0 degree and the roll angle to be 0 degree;
pose 2 represents: the azimuth angle of the carrier is enabled to point to 45 degrees, the pitch angle is 0 degree, and the roll angle is 0 degree;
pose 3 represents: the azimuth angle of the carrier is pointed to 90 degrees, the pitch angle is 0 degree, and the roll angle is 0 degree;
pose 4 represents: enabling the azimuth angle of the carrier to point to 135 degrees, the pitch angle to be 0 degree and the roll angle to be 0 degree;
pose 5 represents: the azimuth angle of the carrier is enabled to point to 180 degrees, the pitch angle is 0 degree, and the roll angle is 0 degree;
pose 6 represents: enabling the azimuth angle of the carrier to point to 225 degrees, the pitch angle to be 0 degree and the roll angle to be 0 degree;
pose 7 represents: enabling the azimuth angle of the carrier to point to 270 degrees, the pitch angle to be 0 degree and the roll angle to be 0 degree;
pose 8 represents: the azimuth angle of the carrier is enabled to point at 315 degrees, the pitch angle is 0 degree, and the roll angle is 0 degree.
The following are specifically mentioned:
a) the plane multipoint calibration method comprises but is not limited to plane 8-point calibration, and corresponding data can be acquired by increasing or decreasing postures according to actual conditions;
b) the azimuth angle expressed in the above-mentioned key points of posture arrangement does not refer to the absolute azimuth angle of the carrier, but refers to a relative angle, for example, when the posture 1 is arranged, the azimuth angle of the magnetic compass can point to any angle, for example, 42 °, but when the posture 2 is arranged, the azimuth angle of the magnetic compass needs to be arranged to be about 87 °, and so on;
c) the pitch angle and the roll angle expressed in the above-mentioned attitude placing key points refer to absolute angles of the carrier relative to a horizontal plane, but when the attitude placing key points are placed in the above attitudes, the azimuth angle, the pitch angle and the roll angle do not need to be particularly strict, and the error of each angle can be accepted within +/-15 degrees;
d) the postures 1 to 8 are described above for convenience, and the data acquisition sequence is not limited in the actual operation process.
For the plane circumference calibration method, the calibration is implemented according to the following steps: the carrier platform is kept horizontal, so that the carrier platform slowly rotates for one circle (rotation azimuth angle) at a constant speed in the Z-axis direction of the vertical axis, can start to rotate at any azimuth angle, and can rotate clockwise or anticlockwise. In the process of uniform and slow rotation, the magnetic compass automatically sends related commands at fixed intervals, and dynamically acquires triaxial magnetic field data in the rotating process.
Whether in plane multipoint calibration or in plane circumferential calibration, one revolution is referred to as one revolution in the carrier platform in a defined area, which is: the minimum area required for one revolution of the device.
After data acquisition is completed, the built-in algorithm of the magnetic compass can automatically complete plane multipoint calibration or plane circumference calibration, an error model is solved, obtained error parameters of the three-axis magnetic sensor are stored, the obtained error parameters of the three-axis magnetic sensor are brought into a formula (8) to obtain calibrated three-axis magnetic field data, and then a real-time azimuth α of the carrier is obtained through calculation of a formula (7).
In summary, the above description is only a preferred embodiment of the present invention, and is not intended to limit the scope of the present invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (8)

1. A magnetic compass calibration method for eliminating carrier magnetic interference is characterized by comprising the following steps:
acquiring three-axis magnetic field data of a magnetic compass under different postures of a carrier platform;
establishing an error model between the three-axis magnetic field data before and after the three-axis magnetic sensor is calibrated, and solving error parameters of the three-axis magnetic sensor in the error model by using the three-axis magnetic field data to obtain an error model;
and thirdly, acquiring triaxial magnetic field data and triaxial acceleration data of the magnetic compass again, substituting the acquired triaxial magnetic field data of the magnetic compass into the error model to obtain calibrated triaxial magnetic field data, solving by combining the triaxial acceleration data to obtain a pitch angle, a roll angle and an azimuth angle of the magnetic compass, and outputting a calibrated attitude angle of the magnetic compass.
2. The method for calibrating a magnetic compass for eliminating magnetic interference of a carrier according to claim 1, wherein the method for solving the azimuth angle comprises the following steps: converting the calibrated three-axis magnetic field data into X, Y-axis magnetic field data under a horizontal coordinate system; and then substituting the magnetic field data in the X, Y axis direction under the horizontal coordinate system into a magnetic azimuth calculation formula to solve the magnetic compass azimuth.
3. The method for calibrating a magnetic compass capable of eliminating magnetic interference on a carrier according to claim 1, wherein the error model in the second step is established by using a poisson model.
4. The method for calibrating a magnetic compass capable of eliminating carrier magnetic interference according to claim 1, wherein the method for solving the error parameters of the three-axis magnetic sensor in the second step specifically comprises:
and taking two norms of the error model to be arranged as a measurement equation of a Kalman filter, taking error parameters of a three-axis magnetic sensor in the error model as state vectors of the Kalman filter, taking a unit matrix as a state transition matrix of the Kalman filter, establishing the Kalman filter equation, solving the Kalman filter equation by utilizing three-axis magnetic field data under more than twelve different postures, and solving to obtain an estimation value of the state vectors, namely the error parameters of the three-axis magnetic sensor.
5. The method for calibrating a magnetic compass capable of eliminating magnetic interference of a carrier according to claim 1, wherein the solving method of pitch angle and roll angle in the three steps is as follows: and calculating by using the transformation relation between the geographic coordinate system and the carrier coordinate system.
6. The method for calibrating a magnetic compass for eliminating magnetic interference of a carrier according to claim 1, wherein the method for acquiring different postures of the carrier platform comprises the following steps:
if the carrier platform is a handheld carrier, rotating the carrier platform in the space, and dynamically acquiring and outputting more than twelve groups of three-axis magnetic field data at fixed time intervals; or changing the posture of the carrier platform, statically acquiring more than twelve groups of three-axis magnetic field data and outputting the data.
7. The method for calibrating a magnetic compass for eliminating magnetic interference of a carrier as set forth in claim 6, wherein the method for rotating in space is: and (3) carrying the carrier by hand, firstly enabling the carrier platform to slowly rotate for one circle around the Z-axis direction of the vertical axis, then rotating for one circle around the Y-axis direction of the pitching axis, and finally rotating for one circle around the X-axis direction of the transverse rolling shaft.
8. The method for calibrating a magnetic compass capable of eliminating magnetic interference of a carrier according to claim 1, wherein if the carrier platform is calibrated in a plane, the carrier platform is rotated in the plane, and more than eight sets of three-axis magnetic field data are dynamically collected and output at fixed time intervals; or changing the posture of the carrier platform, statically acquiring more than eight groups of three-axis magnetic field data and outputting the data.
CN201911358750.5A 2019-12-25 2019-12-25 Magnetic compass calibration method for eliminating carrier magnetic interference Pending CN110954080A (en)

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CN111815939A (en) * 2020-05-21 2020-10-23 摩拜(北京)信息技术有限公司 Parking control method for vehicle and electronic equipment
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CN117537792B (en) * 2024-01-03 2024-04-30 西南应用磁学研究所(中国电子科技集团公司第九研究所) Electronic compass self-adaptive azimuth correction method
CN118670368A (en) * 2024-08-20 2024-09-20 烟台初心航空科技有限公司 Aircraft magnetic compass error calibration method based on gating circulation unit

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Application publication date: 20200403